- EV’s, wind turbines, solar panels are mineral-intensive
- several of these minerals are considered “critical”
- U.S. rapidly expanding mining for “green” technologies
- mining: H20-intensive, toxic wastes that degrade water, air, soil
2022-02-01
what social + environmental dilemmas emerge from the expanding energy transition mining frontier in the U.S.?
map0 <- ggplot() +
geom_polygon(data=state, #add base map
color = "black",
fill="white",
aes(x=long, y=lat, group=group)) +
geom_point(data=minesRaw, #add mines
aes(x=LONGITUDE, y=LATITUDE, color=CRITICAL_MINERAL)) +
theme_minimal()+ #remove grey background
theme(legend.position="none", #remove legend, axes labels/ticks
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank()) +
ggtitle('"Critical Mineral" Mines & Deposits in U.S.') + #title
coord_fixed(1.3) #adjust aspect ratio
ggplotly(map0) #make interactive
data: USGS 2017
map1 <- ggplot() +
geom_polygon(data=state, #add base map
color = "black",
fill="white",
aes(x=long, y=lat, group=group)) +
geom_point(data=minesRaw, #add mines
aes(x=LONGITUDE, y=LATITUDE, color=CRITICAL_MINERAL,
text=paste("",CRITICAL_MINERAL))) +
theme_minimal()+ #remove grey background
theme(legend.position="none", #remove legend, axes labels/ticks
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank()) +
ggtitle('"Critical Mineral" Mines & Deposits in U.S.') + #title
coord_fixed(1.3) #adjust aspect ratio
ggplotly(map1, tooltip="text") %>% #make interactive
style(hoverinfo="none", traces=1)
data: USGS 2017
unique(minesRaw$CRITICAL_MINERAL) %>% as_tibble()
mines <- minesRaw %>% #filter to key energy transition minerals
filter (CRITICAL_MINERAL %in% c("Aluminum",
"Cadmium",
"Cobalt",
"Copper",
"Dysprosium",
"Gallium",
"Indium",
"Lithium",
"Manganese",
"Neodymium",
"Nickel",
"Silver",
"Selenium",
"Tellerium",
"Rare-Earth Elements"))
map2 <- ggplot() +
geom_polygon(data=state, #add base map
color = "black",
fill="white",
aes(x=long, y=lat, group=group)) +
geom_point(data=mines, #add mines
aes(x=LONGITUDE, y=LATITUDE, color=CRITICAL_MINERAL,
text=paste("",CRITICAL_MINERAL))) +
theme_minimal()+ #remove grey background
theme(legend.position="none", #remove legend, axes labels/ticks
axis.title.x=element_blank(),
axis.text.x=element_blank(),
axis.ticks.x=element_blank(),
axis.title.y=element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank()) +
ggtitle('"Critical Mineral" Mines & Deposits in U.S.:<br>Cobalt, Gallium, Lithium, Manganese, Indium') +
coord_fixed(1.3) #adjust aspect ratio
ggplotly(map2, tooltip="text") %>% #make interactive
style(hoverinfo="none", traces=1)
data: USGS 2017
mines %>% #count mines by mineral as_tibble() %>% select(CRITICAL_MINERAL) %>% group_by(CRITICAL_MINERAL) %>% summarize(count=n()) %>% arrange(desc(count))
Q1: where are energy transition mineral mines + deposits located?
Q2: who lives in vicinity to them?
tidycensus packagest_buffer()st_intersects()st_buffer()